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Appendix: Numerical experiments

  • Alexander Rubinov
  • Xiaoqi Yang
Part of the Applied Optimization book series (APOP, volume 85)

Abstract

In this section we present results of numerical experiments from [118] that confirm that numerical methods based on small penalty parameters (see Subsection 4.3.9) can be successfully used for global constrained non-convex optimization.

Keywords

Numerical Experiment Local Search Global Minimizer Lipschitz Function Penalty Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Alexander Rubinov
    • 1
  • Xiaoqi Yang
    • 2
  1. 1.School of Information Technology and Mathematical SciencesUniversity of BallaratVictoriaAustralia
  2. 2.Department of Applied MathematicsHong Kong Polytechnic UniversityHong KongChina

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